Distance detection method and system

ABSTRACT

There is provided a system and method for detecting a distance to an object. The method comprises providing a lighting system having at least one pulse width modulated visible-light source for illumination of a field of view; emitting an illumination signal for illuminating the field of view for a duration of time y using the visible-light source at a time t; integrating a reflection energy for a first time period from a time t−x to a time t+x; determining a first integration value for the first time period; integrating the reflection energy for a second time period from a time t+y−x to a time t+y+x; determining a second integration value for the second time period; calculating a difference value between the first integration value and the second integration value; determining a propagation delay value proportional to the difference value; determining the distance to the object from the propagation delay value.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a reissue continuation application of and claimspriority to U.S. application Ser. No. 14/984,704, filed on Dec. 30,2015, issued as U.S. Pat. No. RE46,930. U.S. application Ser. No.14/984,704, issued as U.S. Pat. No. RE46,930, is a reissue applicationbased on U.S. application Ser. No. 13/632,191, filed on Oct. 1, 2012,which previously issued as U.S. Pat. No. 8,619,241. U.S. applicationSer. No. 13/632,191 is a divisional of U.S. application Ser. No.12/809,235, filed Jun. 18, 2010, now U.S. Pat. No. 8,310,655, which isthe U.S. national phase of International Application No.PCT/CA2008/002268, which claims priority to U.S. Provisional ApplicationSer. No. 61/015,738, filed Dec. 21, 2007, U.S. Provisional ApplicationSer. No. 61/015,867, filed Dec. 21, 2007, and U.S. ProvisionalApplication Ser. No. 61/042,424, filed Apr. 4, 2008.

TECHNICAL FIELD

The invention relates to methods and systems for improving themeasurement of light transit time reflected by different types ofobjects in detection and ranging methods and systems.

BACKGROUND OF THE ART

Several methods are used to measure the distance between an apparatusand an object. Optical range-finding systems frequently rely on thetime-of-flight principle and determine the distance between theapparatus and the object by measuring the time a short pulse of lightemitted from the apparatus takes to reach an object and be reflected toa photo-detection circuit. Conventional optical rangefinders use acounter initiated at the starting pulse and then stopped when thereceiver circuit detects the pulse echo of a value higher than aspecific threshold. This threshold can be set low to provide sensitivitybut the system will generate false alarms from transient noise. It canbe set high to avoid false alarms but the system will not detect objectsthat return weak signal reflection. In bad weather conditions, such asrain or snow, several pulse echoes can be generated. Some techniqueshelp to detect a certain number of echoes and may be used the rejectsome reflections but they have their limitations.

Some optical rangefinders use other methods to be more robust againstfalse alarms. One method is based on the use of an analog-to-digitalconverter (ADC) for the digitalization of the waveform of the echoedback signal. Once digitalized, the waveform can be processed by digitalsignal processing circuits to improve the performance of the system.

Several techniques are already known for improving the performance of anoptical rangefinder using an ADC. Averaging is an efficient way toimprove the signal to noise ratio (SNR). However, averaging has animpact on response time and may render the system too slow for someapplications.

The resolution of distance measurement can be enhanced by using a clockpulsed delay circuit technique. Using an integer (N) division of theclock pulse signal with a delay circuit and by rearranging each echolight pulse sample data, this technique improves the resolution by afactor N. However, this technique has an impact on the number ofaverages if the averaging technique is also used to improve the SNR.

Digital correlation is another digital processing technique forincreasing the resolution of the range measurement. By correlating theecho pulse signal with a pre-stored waveform, the distance to the objectcan be estimated by using the peak value of the result of thecorrelation function.

Several digital processing techniques have been elaborated to improvethe performance of rangefinders but none consider that the need, interms of resolution and signal to noise improvement, is not constant asa function of the range for most of range-finding applications.

SUMMARY

It is therefore an aim of the present invention to address at least oneof the above mentioned difficulties

The present system improves the detection of the presence and themeasure of the distance of objects, while optimizing the performance(resolution, repetition rate, etc) by adapting a range-dependantprocessing as a function of the need of different applications.

The present system can be adapted for use with a lighting system forlighting purposes as well as for the detection and ranging purposes.

The present system also improves the detection of rain, snow, fog, smokeand can provide information about current weather conditions.

According to a broad aspect of the present invention, there is provideda method for detecting a distance to an object. The method comprisesproviding a lighting system having at least one pulse width modulatedvisible-light source for illumination of a field of view; emitting anillumination signal for illuminating the field of view for a duration oftime y using the visible-light source at a time t; integrating areflection energy for a first time period from a time t−x to a time t+x;determining a first integration value for the first time period;integrating the reflection energy for a second time period from a timet+y−x to a time t+y+x; determining a second integration value for thesecond time period; calculating a difference value between the firstintegration value and the second integration value; determining apropagation delay value proportional to the difference value;determining the distance to the object from the propagation delay value.

BRIEF DESCRIPTION OF THE DRAWINGS

Having thus generally described the nature of the invention, referencewill now be made to the accompanying drawings, showing by way ofillustration a preferred embodiment thereof and in which:

FIG. 1 is a block diagram of an embodiment of the lighting system;

FIG. 2 shows an example of a reflected signal with accumulation andphase shift techniques wherein FIG. 2a is a trace obtained with noaccumulation and no phase shift, FIG. 2b has accumulation and phaseshift improvements and FIG. 2c has a greater number of accumulations andphase shifts;

FIG. 3 is a table of example setup parameters for the segmentation;

FIG. 4 shows an example of a reflected signal with adjusted parametersas a function of the distance;

FIG. 5 is a flow chart of an embodiment of the segmentation process;

FIG. 6 shows an example of the accumulation and phase shift techniquefor a 10 m range finder using the one sample by optical pulse technique;

FIG. 7 is a table of example setup configuration for the accumulationand phase shift technique using the one sample by optical pulsetechnique;

FIG. 8 is a block diagram of a lidar module using an embedded processor;

FIG. 9 shows a noisy signal fitted and filtered;

FIG. 10 presents a Gaussian pulse with a zero-crossing point of thefirst derivative;

FIG. 11 shows a typical PWM pattern with slope adjustment;

FIG. 12 shows a rising edge signal from a source and reflected signals;

FIG. 13 shows a 10% to 90% rising edge of an echo back noisy signal withlinear regression;

FIG. 14 is a flow chart of an embodiment of the PWM edge technique fordetection and ranging; and

FIG. 15 shows a rising edge with overshoot stabilizing after one cycleof the resonance frequency;

FIG. 16 shows a timing diagram of the method using an integration signalfrom the reflected signal and synchronized with rising edge and fallingedge of the PWM lighting source;

FIG. 17 is a flow chart of the main steps of a method for acquiring adetected light optical signal and generating an accumulated digitaltrace; and

FIG. 18 is a flow chart of the main steps of a method for detecting adistance to an object.

It will be noted that throughout the appended drawings, like featuresare identified by like reference numerals.

DETAILED DESCRIPTION

FIG. 1 is a block diagram illustrating an embodiment of a lightingsystem equipped with the present system. The lighting system 100 has avisible-light source 112. The visible-light source 12 112 has, as afirst purpose, the emission of visible light for illumination or visualcommunication of information, like signaling, for human vision. Theprimary purpose of emitting light is controlled according to specificcriteria like optical power, field of view and light color, to meetrequirements defined through a number of regulations. In the preferredembodiment, the visible-light source 112 has one or more solid-statelighting devices, LEDs or OLEDs for instance.

The visible-light source 112 is connected to a source controller 114, soas to be driven into producing visible light. In addition to emittinglight, the system 100 performs detection of objects and particles(vehicles, passengers, pedestrians, airborne particles, gases andliquids) when these objects are part of the environment/sceneilluminated by the light source 112. Accordingly, the source controller114 drives the visible-light source 112 in a predetermined mode, suchthat the emitted light takes the form of a light signal, for instance byway of amplitude-modulated or pulsed light emission.

These light signals are such that they can be used to provide thelighting illumination level required by the application, throughdata/signal processor 118 and source controller 114, while producing adetectable signal. Accordingly, it is possible to obtain a light levelequivalent to a continuous light source by modulating the light signalfast enough (e.g., frequency more than 100 Hz) to be generallyimperceptible to the human eye and having an average light powerequivalent to a continuous light source.

In an embodiment, the source controller 114 is designed to provide anillumination drive signal, such as a constant DC signal or a pulse-widthmodulated (PWM) signal, that is normally used in lighting systems toproduce the required illumination and control its intensity. Theillumination drive signal is produced by the illumination driversub-module 114A of the controller 114.

A modulated/pulsed driving signal supplies the fast modulation/pulsesequence required for remote object detection. This modulated/pulseddrive signal is produced by a modulation driver sub-module 114B of thecontroller 114. The amplitude of short-pulse (typ. <50 ns) can beseveral time the nominal value while the duty cycle is low (typ. <0.1%).

The modulator driver 114B can also be used to send data for opticalcommunication. Both driving signals can be produced independently or incombination. Sequencing of the drive signals is controlled by thedata/signal processor 118. The light source 112 can be monitored by theoptical detector 116 and the resulting parameters sent to thedata/signal processor 118 for optimization of data processing.

An alternative for sourcing the light signal for detection involves anauxiliary light source (ALS) 122, which can be a visible or non-visiblesource (e.g., UV or IR light, LEDs or laser) using the modulation driver14B 114B. The auxiliary light source 122 provides additionalcapabilities for detecting objects and particles. UV light source(particularly around 250 nm) can be used to limit the impact of thesunlight when used with a UV detector. IR light can be used to increasethe performance and the range of the detection area. IR lights and othertypes of light can be used to detect several types of particles byselecting specific wavelengths. The auxiliary light source 122 can alsobe useful during the installation of the system by using it as a pointerand distance meter reference. It can also be used to determine thecondition of the lens.

The visible-light source 112 is preferably made up of LEDs. Morespecifically, LEDs are well suited to be used in the lighting system 100since LED intensity can be efficiently modulated/pulsed at suitablespeed. Using this feature, current lighting systems already installedand featuring LEDs for standard lighting applications can be used as thelight source 112 for detection applications, such as presence detectionfor energy savings, distance and speed measurements, fog, rain, snow orsmoke detection and spectroscopic measurements for gas emission or smogdetection.

The system 100 has at least one lens 130 through which light is emittedin an appropriate way for specific applications. At least one input lenssection 130a of at least one lens 130 is used for receiving the lightsignal, for instance reflected or diffused (i.e., backscattered) by theobjects/particles 134. This input lens section 130a can be at a singlelocation or distributed (multiple zone elements) over the lens 130 andhave at least one field of view. Several types of lens 130 can be used,such as Fresnel lenses for example. A sub-section of the lens 130 can beused for infrared wavelength. A sub-section of the lens 130 can be usedfor optical data reception.

A detector 116 is associated with the visible-light source 112 and/orauxiliary light source 122 and the lens 130. The detector module 116 isan optical detector (or detectors) provided so as to collect lightemitted by the light source 112/ALS 122 and back-scattered (reflected)by the objects/particles 134. Detector module 116 can also monitor thevisible-light source 112 or auxiliary light source 122. The light signalcan also come from an object 134 being the direct source of this light(such as a remote control) in order to send information to thedata/signal processor through the optical detector module 116. Theoptical detector module 116 is, for example, composed of photodiodes,avalanche photodiodes (APD), photomultipliers (PMT), complementarymetal-oxide semiconductor (CMOS) or charge-coupled device (CCD) arraysensors.

Filters are typically provided with the detector module 116 to controlbackground ambient light emitted from sources other than the lightingsystem 100. Filters can also be used for spectroscopic measurements andto enhance performance of the light source 112.

A front-end and analog-to-digital converter (ADC) 124 is connected todetector 116 and receives detected light data therefrom and controls thedetector 116. For instance, adjusting the Vbias of an APD detector canbe one of the detector controls to optimize the gain of the receiversection for an Automatic Gain Control (AGC). Analog filters can be usedfor discriminating specific frequencies or to measure the DC level.

A detection and ranging digital processing unit 126 is connected to thefront-end 124, and controls parameters such as gain of amplifier,synchronization and sample rate of the ADC. The detection and rangingdigital processing unit 126 receives data from ADC and pre-processes thedata.

The data/signal processor 118 is connected to the detection and rangingprocessing module 126 and receives pre-processed data. The data/signalprocessor 118 is also connected to the source controller 114, so as toreceive driving data therefrom. The data/signal processor 118 has aprocessing unit (e.g., CPU) so as to interpret the pre-processed datafrom the detection module 126, in comparison with the driving data ofthe source controller 114, which provides information about thepredetermined mode of emission of the light signals emitted by thevisible-light source 112.

Accordingly, information about the object (e.g., presence, distance,speed of displacement, composition, dimension, etc.) is calculated bythe data/signal processor 118 as a function of the relationship (e.g.,phase difference, relative intensity, spectral content, time of flight,etc.) between the driving data and the detected light data, isoptionally pre-processed by the front-end and ADC 24 124 and thedetection and ranging processing unit 126. A database 120 may beprovided in association with the data/signal processor 118 so as toprovide historical data or tabulated data to accelerate the calculationof the object parameters.

In view of the calculation it performs, the data/signal processor 118controls the source controller 114 and thus the light output of thevisible-light source 112. For instance, the visible-light source 112 maybe required to increase or reduce its intensity, or change theparameters of its output. For example, changes in its output power canadapt the lighting level required in daytime conditions versus nighttimeconditions or in bad visibility conditions such as fog, snow or rain.

The system 100 can be provided with sensors 132 connected to thedata/signal processor 118. Sensors 132 can be an inclinometer,accelerometer, temperature sensor, day/night sensors, etc. Sensors 132can be useful during the installation of the system and during operationof the system. For example, data from an inclinometer and accelerometercan be used to compensate for the impact on the field of view of aneffect of the wind or any kind of vibration. Temperature sensors areuseful to provide information about weather (internal, external orremote temperature with FIR lens). Information from sensors 132 anddata/signal processor 118 and light from light source 112 and auxiliarylight source 122 can be used during installation, in particular foradjusting the field of view of the optical receiver. The auxiliary lightsource 112 122 can be used as a pointer and distance meter.

The system 100 has a power supply and interface 128. The interfacesection is connected to a Data/signal processor and communicates to anexternal traffic management system 140 (via wireless, power line,Ethernet, CAN bus, USB, etc.).

Segmentation of the Digital Processing as a Function of the Range

Several range finding applications need different performances as afunction of the range. For automotive applications, such as AdaptiveCruise Control (ACC), it could be useful to detect a vehicle more than100 meters ahead but the needs in terms of accuracy and repetition rateare not the same as for short range applications such as pre-crashmitigation. Basically, for a short range application, the reflectedsignal is strong but, usually, the needs for a good resolution and fastrefresh rate of the data are high. For a long range application, theopposite is true, the reflected signal is weak and noisy but the needfor resolution and refresh rate is less demanding.

Phase shifting control techniques can improve accuracy using a digitalacquisition system with low sample rate. For instance, a relatively lowcost ADC (ex.: 50 MSPS) can have an improved temporal resolution ifsuccessive acquisitions are delayed by an equivalent fraction of theacquisition time period but this technique has an impact on SNR andrefresh rate when averaging is used.

To optimize the performance, one can adjust specific parameters as afunction of the distance. Using the detection and ranging digitalprocessing unit 126 and the Data/signal Processor 118, allows to controlthe number of shift delay by period, the number of accumulation and therefresh rate for each data point sampled or for several segments. Forshorter distances, with an echo back signal which is relatively strong,the number of shift delays and the refresh rate can be higher to improvethe resolution and the response time. The number of accumulation (orother time-integration techniques) would be lower but sufficient atshort distances (trade-off between signal-to-noise ratio, resolution andnumber of results per second).

The accumulation technique improves the signal-to-noise ratio of thedetected light signal using multiple measurements. In order to produceone distance measurement, the technique uses M light pulses and for eachlight pulse, a signal detected by the optical detector is sampled by theADC with an ADC time resolution of 1/F second thereby generating M lidartraces of j points (S₁ to S_(j)) each. Points of the M lidar traces areadded point per point to generate one accumulated digital lidar trace ofj points.

The phase shift technique is used to improve the time resolution of thetrace acquired by the ADC and limited by its sample rate F Hz. The phaseshift technique allows for the use of a low cost ADC having a low samplerate F by virtually increasing the effective sample rate. The effectivesample rate is increased by a factor P by acquiring P sets correspondingto P light pulses while shifting the phase between the emitted lightpulse and the ADC sampling rate. The phase shifting between eachacquisition corresponds to 2π/P. The P sets obtained are then combinedin a single trace by interleaving the P sets such that the resultingtrace is equivalent to a single measurement with a temporal resolution(1/F×P) second.

By combining the accumulation and the phase shift techniques, anaccumulation of M sets is performed for each one of the P phase shifts,for a total of N=M×P acquisition sets. Using the N sets, the detectionand ranging digital processing unit 126 and the Data/signal Processor118 creates one combined trace of the reflected light pulse. Each pointin the combined trace is an accumulation of M=N/P sets and the effectivetime resolution of the combined trace is 1/(F×P) second. To store onecomplete trace, the length of the buffer is at least j×P elements andthe number of bit of each element is a function of the resolution of theADC (number of bits, B) and the number of accumulations M. To preventoverflow, each element of the buffer should have at least B+log₂M bits.Example results of the accumulation and phase shift techniques are shownin FIGS. 2a, 2b and 2c. For that experimentation, a target isapproximately at a distance of 12 meters and the system use an ADC at 50MSPS. FIG. 2a shows a trace obtained with no accumulation and no phaseshift. The signal is noisy with a lack of resolution and it is verydifficult to identify the target. FIG. 2b shows an improvement in termsof signal to noise ratio by accumulating 64 sets with 8 shift delays.Finally, FIG. 2c shows how an accumulation of 1024 sets with 256 shiftdelays can improve the signal-to-noise ratio and resolution.

Accumulation and shift control can be done by a programmable logic, aField Programmable Gate Array (FPGA) for example. Phase shifting can becontrolled by delaying the clock of the ADC converter 130 by a fractionof a period or by delaying the driver of the optical source.

FIG. 3 shows one example of setup configurations for this method usingdifferent parameters as a function of the distance. For differentdistances (for instance, for a range from 1 m to 100 m), one canoptimize the temporal resolution, the number of accumulation and therefresh rate and make tradeoffs in terms of sensibility, accuracy andspeed as a function of the distance to a target.

FIG. 4 shows a reflected signal with a first echo from an object closerto the system and a second echo from another object further from thesource. The amplitude of the first echo is higher and the systemoptimizes the temporal resolution. The amplitude of the second echo backpulse from the farther object is lower and the system optimizes the SNRby using more accumulation instead of optimizing the resolution.

The value of each parameter can be adaptive as a function of the echoback signal. After analyzing the level of the noise, the system canoptimize the process by adjusting parameters as a function of thepriority (resolution, refresh rate, SNR). For example, if the noise islower than expected, the system can reduce the number of accumulationand increase the number of shift delays to improve the resolution.

FIG. 5 shows a flow chart of a typical process for this method. In thisflowchart and in all other flowcharts of the present application, somesteps may be optional. Some optional steps are identified by using adashed box for the step. Configuration 500 sets several parametersbefore the beginning of the process. Acquisition 502 starts the processby the synchronization of the emission of the optical pulses and theacquisition of samples by the ADC. Digital filtering and processing ofthe data 504 make the conditioning for the extraction and storage inmemory of a lidar trace 506. Detection and estimation of the distance508 is made, typically using a reference signal and measuring the lapseof time between the emission and the reception of the signal. Thetransmission of the results 510 (the detection and the estimation of thedistance) are transmitted to a external system. Noise analysis 512 isperformed and an adjustment of the parameters as a function of the levelof the noise 514 can be made to optimize the process.

Based on shift delay and accumulation techniques, it is possible tooptimize the cost of optical range finder systems particularly for shortrange distance measurement. By using only one sample per optical pulse,the ADC has to acquire samples at the frequency of the optical pulseemission. For a system driving optical pulses at L Hz, the ADC convertsL samples per second with P shift delay of D ns of delay. FIG. 6 showsan example of that technique for a ten meter range finder. The sourceemits a 20 ns optical pulse at T=0 ns at several KHz (ex.: 100 KHz). Inthe air, the optical pulse takes approximately 65 ns to reach a targetat ten meters and to reflect back to the sensor of the system. Each timea pulse is emitted, the ADC acquires only one sample. The ADC works atsame frequency as the optical pulse driver (ex.: 100 KHz). For each oneof the first twenty optical pulses, the system synchronizes a shiftdelay of 5 ns between the optical pulse driver and the ADC. After 20pulses, the system samples the reflected back signal 95 ns after thepulse was emitted, just enough to detect the end of the reflected backsignal from a target at 10 meters. For this example, if the system worksat 100 KHz, after 200 us, a complete 10 meters Lidar trace is recorded.To improve the signal-to-noise ratio, one can accumulate up to 5000times to have one complete lidar trace per second. FIG. 7 is a tableshowing setup configuration for this method. For a maximum range of 10meters and 30 meters, the table shows tradeoffs between accuracy(temporal resolution), sensibility (improvement of the signal to noiseratio by accumulation) and speed (refresh rate).

Nowadays, embedded processors, microcontrollers and digital signalprocessor, have a lot of processing power with fixed-point orfloating-point units with hundreds of Mega FLOating point Operations perSecond (MFLOPS) of performance. They are highly integrated withanalog-to-digital converters, timers, PWM modules and, several types ofinterface (USB, Ethernet, CAN bus, etc). Using the last techniquedescribed, mainly because the requirement in terms of speed of the ADCis low, the major part of the range finder system can be integrated inan embedded processor. FIG. 8 shows a block diagram of a lidar module800 using an embedded processor optimizing the cost of the range findersystem. The embedded processor 801 controls the timing for the driver802 sourcing the light source 803. A light signal is emitted in adirection determined by the optical lens 804. A reflection signal fromobjects/particles 834 806 is received on the optical lens 804 andcollected by the optical detector and amplifier 805. The embeddedprocessor 801 uses an embedded ADC to make the acquisition of the lidartrace and processes the data and sends the information to an externalsystem 840 808. The system 800 can use several sources being drivensequentially using one sensor or several sensors. The frequency ofacquisition is at the frequency of optical source multiplied by thenumber of optical sources.

Moving Average, Filters, Frequency Analysis and Peak Detection

Instead of collecting N data and then performing an average (one averageat each 1/N×[frequency of the source]), moving average techniques permitto constantly have the last N samples to perform an average. Using aFIFO by adding a new data and subtracting the first data accumulated isan example of an implementation of that technique.

Using too much integration time for averaging can generate a problemwhen detecting moving objects. Averaging techniques can consider asignal from moving objects as noise and will fail to discriminate it.Frequency domain analysis can be useful for this kind of situation.Wavelet transform is very efficient for signal analysis intime/frequency domain and is sensitive to the transient signals. Byseparating the echo back signal in several segments and analyzing thespectral frequency, the system can detect the frequency of the pulse ofthe source in a specific segment. Averaging parameters can be adjustedas a function of events detected by the spectral analysis process. Forinstance, the number of averages should be reduced when moving objectsare detected sequentially in different segments.

Low pass filters can be used as pre-processes on each trace beforeaveraging. Filters may be particularly efficient when more than onesample is available on an echo pulse. Information from noise analysisand from the information of the signal waveform emitted by the sourcecan also help to discriminate a signal and to adjust the parameters.Specific processing functions can be used for each point of the trace orby segment.

Another way to optimize the detection of an object and the measurementof the distance is using a reference signal and making a fit with thelidar trace. The reference signal can be a pattern signal stored inmemory or a reference reflection signal of an optical pulse detected bya reference optical detector. This reference optical detector acquires areference zero value and this reference signal is compared to the lidartrace. Detection and distance is based on comparison between bothsignals. Fit can be made by convolution.

FIG. 9 shows a noisy signal fitted and filtered to diminish the effectsof the noise. FIG. 9 presents the effect of signal filtering and curvefitting. The raw data curve is the noisy signal as received from thesensor. The filter curve is the raw data curve after filtering bycorrelation with an ideal (no noise) pulse. This removes thehigh-frequency noise. Finally the fit curve presents the optimal fittingof an ideal pulse on the filtered signal. Fitting can improve distancestability especially when the signal is weak and still too noisy evenafter filtering.

When a signal waveform has a Gaussian profile, it is possible to use amethod based on a zero-crossing point of the first derivative to detectthe peak of the waveform. This technique requires a previous filteringto remove the noise. When the detection of an event (echo back pulsefrom an object) occurs, the system will detect N consecutive points overa predetermined threshold. The value of N depends notably on the samplerate and the width of the pulse from the source. By computing the firstderivative of those selected points and interpolating to find thezero-crossing point, an estimation of the peak of the signal can befound.

FIG. 10 shows an example of a Gaussian pulse with selected data over apredefined threshold and the result from the derivative calculation ofthose selected data. One can see the zero crossing from the derivativeplot representing the peak of the pulse.

Illumination Driver as a Source for Rangefinder with Edge Detection

Switch-mode LED drivers are very useful notably for their efficiencycompared to linear drivers. PWMs permit a very high dimming ratiowithout drifting the wavelength usually generated by linear drivers.Their performance is particularly well suited for high power LEDs.However, switch-mode LED drivers are noisier and the EMI can be an issuefor some applications. One way to address this issue is to use a gaterising/falling slope adjust circuit to decrease the speed oftransitions. Transitions at lower speed mean less EMI. FIG. 11 presentsa typical PWM signal with slope adjustment.

For range-finding applications, the rapid transition of the signal isgenerally required. Usually, to get good performance, electroniccircuits need to detect fast transition signals within a few nanosecondof resolution. Using a LED light source with a PWM driver withadjustment to diminish the speed of the slope as the source fordetection and ranging is, in principle, not very helpful.

One solution is to use the same LED light source for illumination andfor detection and ranging with a PWM circuit controlling the intensityof illumination. The PWM LED light source has a relatively constantslope during its rising/falling edge to reduce EMI (rising/falling edgeof 100 ns for example). The optical signal from the source is sampled tobe able to determine the starting time of the pulse (T0). Electricalsynchronization signal can also be used to indicate the starting point.The reflected signal is sampled with enough temporal resolution to haveseveral points during the slope of the signal when an object in thefield of view returns a perceptible echo.

FIG. 12 shows an example of a rising edge from a source, an echo backsignal from an object 4.5 meters away from the source (≈30 ns later) andanother from an object at 7 meters from the source (≈45 ns later).Calculating the slope by linear regression or other means, an evaluationof the origin of the signal is made and the elapsed time between thesignal from the source and an echo back signal can be determined. Basedon that result, one can estimate the presence and the distance of theobject reflecting the signal.

FIG. 13 represents a 10% to 90% rising edge of an echo back noisy signalfrom an object at 4.5 meters from the source. With linear regression,one can calculate the intercept point and get a good estimate of thedelay between the two signals. Samples close to the end of the slopehave a better SNR. One can determine different weights in thecalculation as a function of the level of the noise. Both rising andfalling edges can be used. During the calibration process, a thresholdcan be set to discriminate the presence or the absence of an object.Averaging and filtering techniques can be used to diminish the level ofnoise and shifting techniques can also be used to have more points inthe slope. As shown in FIG. 9 , even with a noisy signal, this methodcan give good results.

FIG. 14 shows a flow chart of the typical process for this method. Theecho back signal is filtered 1400, typically using a band-pass filterbased on the frequency of the transition. Rising and falling edges aredetected 1402 and samples are taken in the slope 1404 to memorize adigital waveform of the slope. The calculation of the linear regression1406 is made and permits to calculate the intercept point 1408. Based onthat information, the calculation of the difference in time between thesignal emission and the signal received 1410 allows to estimate thedistance to the object 1412.

This method can be improved by using demodulation and spectral analysistechniques. The base frequency of the PWM can be demodulated and theresult of this demodulation will give an indication of a presence of anobject. By selecting a frequency based on an harmonic coming from theslopes of the PWM signal, one can estimate the position of the object byspectral analysis of different segments. Knowing the approximatedposition, the acquisition of samples will be adjusted to target therising and the falling edge.

By using the edge detection technique, one can use a standard LED driverfor the purpose of lighting and also for the purpose of detection andranging. The frequency of the PWM might be in the range from a few KHzup to 1 MHz. High frequency modulation can improve the SNR notably byaveraging techniques. When the optical output of the source is coupledby optical path (reflection from lens or mirror or use of fiber optic),this method permits using a PWM source for a LED lighting systemcompletely electrically isolated from the receiver.

Other types of rising/falling edge detection can be used with thismethod with the appropriate curve fitting technique. If EMI is not anissue, the electronic driver can generate a fast rising edge and/orfalling edge with some overshoot at a resonance frequency. This signaladds more power at a specific frequency and increase the signal that canbe detected by the receiver. FIG. 15 shows a rising edge with overshootstabilizing after one cycle of the resonance frequency.

Recognition of Predetermined Patterns

Different shapes of objects reflect a modified waveform of the originalsignal. The echo back signal from a wall is different when compared tothe echo back signal from an object with an irregular shape. Reflectionfrom two objects with a short longitudinal distance between them alsogenerates a distinct waveform. By memorizing in database a several typesof waveforms, this data can be used to improve the digital processingperformance. Digital correlation can be done to detect a predeterminedpattern.

Tracking

Averaging techniques do not perform very well with moving objects. Bytracking a moving object, one can anticipate the position of the objectand adapt to the situation. Averaging with shifting proportional to theestimated position is a way to improve the SNR even in the case ofmoving objects. Tracking edges is another way to adjust the acquisitionof the waveform with more points in the region of interest. Spectralanalysis can also be used to lock and track an object.

Weather Information and Condition Monitoring

The system can be used as a road weather information system (RWIS) andthus provide information about temperature, visibility (fog, snow, rain,dust), condition of the road (icy) and pollution (smog). Patternrecognition based on low frequency signals and spikes can be implementedto do so. The recognition of bad weather condition patterns helps todiscriminate noise from objects. The system can be used to adjust theintensity of light depending on weather conditions. Monitoring thecondition of the lens is also possible (dirt, accumulation of snow,etc). This monitoring can be done by the measurement of the reflectionon the lens from the source or from an auxiliary source.

Detection Based on Integration Time

FIG. 16 shows a timing diagram of the method using an integration signalfrom the reflected signal and synchronized with the rising edge and thefalling edge of the PWM lighting source.

This method uses a sensor or an array of sensors (1D or 2D array—CCD,CMOS) with an integrator, or electronic shutter, and a PWM light sourceor a pulsed auxiliary light source. FIG. 16 shows a PWM signal (PWMcurve 1601) with an adjustable duty cycle to control the intensity oflight for illumination purposes. Before the rising edge of the PWMpulse, at time t−x, the sensor starts the integration (sensorintegration curve 1603) of the reflected signal. At time t+x, the sensorstops the integration. The same process is performed at the falling edgeof the PWM. The light pulse from the source is delayed (delay curve1602) proportionally to the travelled distance. The delta curve 1604shows that the integration P1 for the rising edge is smaller than theintegration P2 for the falling edge because of the delay of travel ofthe light signal. In fact, if an object is very close to the source, theintegration value from the rising edge will be approximately equal tothe integration value from the falling edge. But, if an object isfurther, the integration value of rising edge will be less than theintegration value of the falling edge. The difference between the valuesis proportional to the distance. The relationship is:Distance=c×(INT/4)*(P2−P1)/(P2+P1),where c represents the velocity of light, INT represents the integrationtime, P1 represents the integration value synchronized with the risingedge of the optical pulse and P2 represents the integration valuesynchronized on the falling edge of the optical pulse.

When an illumination background from other lighting sources is notnegligible, measurement of the background B during an integration timeINT when the optical source of the system is off can be made andsubtracted from each integration value P1 and P2. The relationship withnon negligible background is:Distance=c×(INT/4)*((P2−B)−(P1−-B))/(P2+P1−2B),where B is the integration value of the optical background level whenthe optical source of the system is off.

In the case where the integration time is larger than the width of thepulse of the optical source, the same technique can be used by switchingthe synchronisation of the signal of the optical source and the signalto the sensor integration time. The result becomes:Distance=c×(INT/4)*(P1−P2)/(P2+P1),where c represents the velocity of light, INT represents the integrationtime, P1 represents the integration value when optical pulse issynchronized with the rising edge of integration and P2 represents theintegration value when the optical pulse is synchronized with thefalling edge of integration.

When an illumination background from other lighting sources is notnegligible, the relationship is:Distance=c×(INT/4)*((P1−B)−(P2−B))/(P2+P1−2B).

Values from the signal integration are memorized. In the case of anarray of sensors, each “pixel” is memorized. Several integrations can beperformed and an averaging process can be done to improve signal tonoise ratio. In the case of an array, we also can improve signal tonoise ratio by using a groups of pixel and combining them to form alarger pixel (binning)

In summary, with reference to FIG. 17 , the main steps of the method foracquiring a detected light optical signal and generating an accumulateddigital trace are shown. The method comprises providing a light sourcewith an optical detector for illumination of a field of view 1700;providing an analog-to-digital converter (ADC) 1702; emitting one pulsefrom the light source in the field of view 1704; detecting a reflectionsignal of the pulse by the optical detector 1706; acquiring j points forthe detected reflection signal by the ADC 1708; storing, in a buffer,the digital signal waveform of j points 1710; introducing a phase shiftof 2π/P 1712; repeating, P times 1714, the steps of emitting 1704,detecting 1706, acquiring 1708, storing 1710 and introducing 1712 tostore 1710, in the buffer, an interleaved waveform of P×j points;accumulating 1716 M traces of interleaved P×j points for a total ofN=M×P acquisition sets, N being a total number of pulses emitted;creating one combined trace of the reflected signal of j×P points byadding each point of the M traces 1718.

Additionally, the combined trace can be compared 1720 to a detectedreference reflection signal of the pulse to determine 1722 a distancetraveled by the pulse.

Alternatively, a timer can be triggered to calculate a time elapsed 1724between the emission of the pulse and the detection of the reflectionsignal to determine a distance traveled 1722 by the pulse based on thetime elapsed.

In summary, with reference to FIG. 18 , the main steps of the method fordetecting a distance to an object are shown. The method comprisesproviding a lighting system 1800 having at least one pulse widthmodulated visible-light source for illumination of a field of view;emitting an illumination signal 1802 for illuminating the field of viewfor a duration of time y using the visible-light source at a time t;integrating a reflection energy for a first time period from a time t−xto a time t+x 1808; determining a first integration value for the firsttime period 1810; integrating the reflection energy for a second timeperiod from a time t+y−x to a time t+y+x 1812; determining a secondintegration value for the second time period 1814; calculating adifference value between the first integration value and the secondintegration value 1816; determining a propagation delay valueproportional to the difference value 1818; determining the distance tothe object from the propagation delay value 1820.

While illustrated in the block diagrams as groups of discrete componentscommunicating with each other via distinct data signal connections, itwill be understood by those skilled in the art that the illustratedembodiments may be provided by a combination of hardware and softwarecomponents, with some components being implemented by a given functionor operation of a hardware or software system, and many of the datapaths illustrated being implemented by data communication within acomputer application or operating system. The structure illustrated isthus provided for efficiency of teaching the described embodiment.

What is claimed is:
 1. A method for detecting a distance to an object,comprising: providing a lighting system having at least one pulse widthmodulated visible-light source for illumination of a field of view;emitting an illumination signal for illuminating said field of view fora duration of time y using said visible-light source at a time t, saidtime t being a center of a transition from a non-illuminated state to anilluminated state of said field of view, for at least one pulse;starting an optical sensor for integrating a reflection energy capturedby said visible-light source, of a reflection of said illuminationsignal, for a first time period at a time t−x of a first one of said atleast one pulse; stopping said optical sensor for said first time periodat a time t+x for said first one of said at least one pulse anddetermining a first integration value for said first time period;starting said optical sensor for integrating said reflection energycaptured by said visible-light source, of said reflection of saidillumination signal, for a second time period at a time t+y−x for asecond one of said at least one pulse, said second one being one of saidfirst one and another one of said at least one pulse, y being greaterthan x; stopping said optical sensor for said second time period at atime t+y+x for said second one of said at least one pulse anddetermining a second integration value for said second time period;measuring a background integration value for non-negligible illuminationbackground from other lighting sources during an integration time 2xwhen said visible-light source is not emitting; subtracting from eachsaid first integration value and said second integration value saidbackground integration value to obtain background compensated firstintegration value and second integration value; calculating a differencevalue between said background compensated first integration value andsaid background compensated second integration value; determining apropagation delay value proportional to said difference value;determining said distance to said object from said propagation delayvalue.
 2. A method as claimed in claim 1, further comprising: providinga threshold distance to a pre-identified object; comparing said distanceto said object with said threshold distance; determining said object tobe said pre-identified object if said comparison is positive.
 3. Amethod as claimed in claim 1, further comprising, when said x is greaterthan said y, said integrating being larger than a width of the pulse,switching a synchronisation of said illumination signal with saidstarting said optical sensor.
 4. A ranging system comprising: a. adriver circuit configured to produce a driving signal for causing alight source to emit pulsed light toward a scene containing an object,b. an optical detector configured to collect pulsed light emitted fromthe light source and back-scattered from the object and to produce anoutput signal conveying acquisitions of light pulses, c. an adaptivesignal processing system coupled to the optical detector, configured toperform an adaptive processing of the output signal, including: (i)sampling the output signal to obtain sampled acquisitions of lightpulses, (ii) performing an accumulation of a number of the sampledacquisitions of light pulses to define an accumulated digital signalvarying with time, the accumulation of the number of the sampledacquisitions of light pulses including performing integration over timeof the number of sampled acquisitions of light pulses, (iii) varying thenumber of accumulated sampled acquisitions of light pulses to obtain amodified accumulated digital signal, based on a parameter of the object,(iv) obtaining a distance measurement from the modified accumulateddigital signal.
 5. The ranging system of claim 4, wherein theaccumulated digital signal defines a signal trace with a pulse-shapedsegment.
 6. The ranging system of claim 5, wherein the signal processingsystem is configured for adjusting an intensity of the driving signalbased on the estimated distance to the object.
 7. The ranging system ofclaim 5, wherein the light is non-visible light.
 8. The ranging systemof claim 4, wherein the parameter of the object includes a distance tothe object, the processing of the output signal comprises increasing thenumber of accumulated sampled acquisitions of light pulses to obtain adistance measurement, with an increasing distance to the object.
 9. Theranging system of claim 4, wherein the parameter of the object includesa distance to the object, the processing of the output signal comprisesdecreasing the number of accumulated sampled acquisitions of lightpulses to obtain a distance measurement, with a decreasing distance tothe object.
 10. The ranging system as defined in claim 4, wherein theoptical detector comprises an array of pixels, each pixel outputting arespective output signal.
 11. The ranging system as defined in claim 10,wherein the array is a 2D array.
 12. The ranging system as defined inclaim 11, wherein the array is a 1D array.
 13. The ranging system asdefined in claim 4, wherein the sampled acquisitions of light pulsesinclude respective sets of j points, the accumulation of the number ofsampled acquisitions of light pulses including adding the number of setsof j points, point by point to generate the accumulated digital signal.14. The ranging system as defined in claim 13, wherein the processing ofthe output signal includes phase-shifting the sampled acquisitions oflight pulses.